diff --git a/recopytex/dashboard/pages/exams_scores/app.py b/recopytex/dashboard/pages/exams_scores/app.py
index 1144de7..3f9139f 100644
--- a/recopytex/dashboard/pages/exams_scores/app.py
+++ b/recopytex/dashboard/pages/exams_scores/app.py
@@ -64,6 +64,14 @@ layout = html.Div(
                             ],
                             id="score_statistics_table_container",
                         ),
+                        html.Div(
+                            children=[
+                                dcc.Graph(
+                                    id="fig_exam_histo",
+                                )
+                            ],
+                            id="fig_exam_histo_container",
+                        ),
                     ],
                     id="analysis",
                 ),
diff --git a/recopytex/dashboard/pages/exams_scores/callbacks.py b/recopytex/dashboard/pages/exams_scores/callbacks.py
index 7fe07a5..938ea14 100644
--- a/recopytex/dashboard/pages/exams_scores/callbacks.py
+++ b/recopytex/dashboard/pages/exams_scores/callbacks.py
@@ -3,9 +3,11 @@
 
 from dash.dependencies import Input, Output, State
 from dash.exceptions import PreventUpdate
+import plotly.graph_objects as go
 import dash_table
 import json
 import pandas as pd
+import numpy as np
 
 from recopytex.dashboard.app import app
 from recopytex.dashboard.common.formating import highlight_scores
@@ -109,3 +111,47 @@ def update_statictics_table(finale_score):
         [{"id": c, "name": c} for c in statistics.columns],
         statistics.to_dict("records"),
     ]
+
+
+@app.callback(
+    [
+        Output("fig_exam_histo", "figure"),
+    ],
+    [
+        Input("final_score_table", "data"),
+    ],
+)
+def update_exam_histo(finale_scores):
+    scores = pd.DataFrame.from_records(finale_scores)
+
+    if scores.empty:
+        return [go.Figure(data=[go.Scatter(x=[], y=[])])]
+
+    ranges = np.linspace(
+        -0.5,
+        scores["score_rate"].max(),
+        int(scores["score_rate"].max() * 2 + 2),
+    )
+
+    bins = pd.cut(scores["mark"], ranges)
+    scores["Bin"] = bins
+    grouped = (
+        scores.reset_index()
+        .groupby("Bin")
+        .agg({"score_rate": "count", "student_name": lambda x: "\n".join(x)})
+    )
+    grouped.index = grouped.index.map(lambda i: i.right)
+    fig = go.Figure()
+    fig.add_bar(
+        x=grouped.index,
+        y=grouped["score_rate"],
+        text=grouped["student_name"],
+        textposition="auto",
+        hovertemplate="",
+        marker_color="#4E89DE",
+    )
+    fig.update_layout(
+        height=300,
+        margin=dict(l=5, r=5, b=5, t=5),
+    )
+    return [fig]